Dynamic random access memories (DRAMs) have been widely used in for example personal computers, monitor interface circuits, input/output control interface circuits and other computer peripheral devices. Since these circuits or devices require different electric characteristics, the DRAMs adopted in these different circuits have to have different electric characteristics. Thus, the DRAMs have to be classified in advance in accordance with the characteristic values thereof to facilitate adoption in different circuits and to meet different electric requirements thereof.
Conventionally, the DRAMs are tested and classified manually which is not only time-consuming and labor-intensive, making the cost of the DRAMs high, but is also subject to error caused by human factors. Thus the DRAMs that are manually tested and classified as the same class or grade may still have a great difference in performance therebetween and thus affecting the correctness of the classification operation.
Thus, it is desirable to provide a DRAM classification method which is carried out automatically and the DRAMs so tested and classified are individually collected in accordance with the class thereof associated with the test result so as to overcome the deficiencies encountered in the prior art.